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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Related Experiment Video

Updated: Apr 28, 2026

Clinical Imaging of Microwave Mammography
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A TV-BM3D Iterative Algorithm for VMAT-CT Reconstruction.

Chia-Lung Chien1, Beibei Guo2, Rui Zhang3,4

  • 1Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.

Journal of Imaging
|April 27, 2026
PubMed
Summary

A new iterative algorithm combining total variation (TV) with block-matching and 3D filtering (BM3D) significantly improves volumetric modulated arc therapy-computed tomography (VMAT-CT) image quality and reconstruction success rates. This advanced VMAT-CT imaging tool enhances onsite imaging for radiotherapy.

Keywords:
block-matching and 3D filteringcompressed sensingcomputed tomographyiterative reconstructiontotal variationvolumetric modulated arc therapy

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Area of Science:

  • Medical Physics
  • Radiotherapy Imaging
  • Image Reconstruction

Background:

  • Volumetric modulated arc therapy-computed tomography (VMAT-CT) uses portal images for onsite imaging during VMAT.
  • Current reconstruction methods like Feldkamp-Davis-Kress (FDK) have limitations in image quality and reconstruction success rates.
  • Improving VMAT-CT is crucial for effective treatment monitoring and adaptive radiotherapy.

Purpose of the Study:

  • To propose an iterative reconstruction algorithm to enhance VMAT-CT image quality.
  • To reduce the number of failed VMAT-CT reconstructions.
  • To evaluate the performance of the proposed algorithm against existing methods.

Main Methods:

  • Developed a novel iterative algorithm combining total variation (TV) with block-matching and 3D filtering (BM3D).
  • Addressed the L1-L2 regularization problem using the split Bregman method.
  • Reconstructed VMAT-CT images from 50 phantom and 17 real-patient portal images using both TV-BM3D and FDK algorithms, with and without preprocessing.

Main Results:

  • The TV-BM3D iterative algorithm achieved higher reconstruction success rates: 48/50 phantom cases and 15/17 patient cases.
  • Compared to FDK (39/50 phantom, 8/17 patient) and FDK with preprocessing (44/50 phantom, 11/17 patient), TV-BM3D showed superior performance.
  • The TV-BM3D algorithm significantly improved VMAT-CT image quality across all treatment sites.

Conclusions:

  • The proposed iterative TV-BM3D algorithm is the first of its kind for VMAT-CT reconstruction.
  • This algorithm offers superior success rates and image quality compared to FDK-based methods.
  • VMAT-CT reconstructed with this advanced algorithm is a promising tool for onsite imaging, treatment monitoring, and adaptive radiotherapy.